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首页> 外文期刊>Natural Hazards >'Internet plus ' approach to mapping exposure and seismic vulnerability of buildings in a context of rapid socioeconomic growth: a case study in Tangshan, China
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'Internet plus ' approach to mapping exposure and seismic vulnerability of buildings in a context of rapid socioeconomic growth: a case study in Tangshan, China

机译:在社会经济快速增长的背景下,“互联网加”方法绘制建筑物的暴露和地震脆弱性:中国唐山的案例研究

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摘要

This paper presents the development of an "Internet+" approach to mapping exposure and seismic vulnerability of buildings in a context of rapid socioeconomic growth. This approach is a combination of the following interdependent components: (1) extraction of footprint areas of a large number of buildings from high-resolution Google Earth images; (2) estimation of floor numbers of these buildings with an integrated use of high-resolution Google Earth images, Tencent/Baidu Street Views, crowdsourcing data, and associated building-relevant local knowledge; and (3) identification of structural types of these buildings by a combined use of crowdsourcing data and associated building-relevant local knowledge. The efficacy of this "Internet+" approach was demonstrated through an application in Tangshan, China. Field-based verification indicated that the overall mean absolute percentage error of the proposed "Internet+" approach in assessing the total floor area of the addressed buildings was 4.64 . The verification also showed that the overall consistency between the estimated structural types using the proposed approach and the actual structural types of the buildings with structural type uncertainties could reach 97.54 , with a kappa coefficient of 0.94. Because of its good accuracy, noteworthy speed, substantial labor savings, negligible cost and distinctive capability in covering large areas in near real time, this "Internet+" approach might have promising prospects in actual seismic loss risk reduction challenges.
机译:本文介绍了在社会经济快速增长的背景下,开发一种“互联网+”方法来绘制建筑物的暴露和地震脆弱性。这种方法是以下相互依存的组成部分的组合:(1)从高分辨率的Google Earth图像中提取大量建筑物的足迹区域;(2)综合使用高分辨率谷歌地球图像、腾讯/百度街景、众包数据以及与建筑物相关的本地知识,估算这些建筑物的楼层数;(3)通过结合使用众包数据和相关的建筑相关当地知识来识别这些建筑物的结构类型。这种“互联网+”方法的有效性通过中国唐山的一个应用得到了证明。实地核查结果显示,所建议的“互联网+”方法在评估所涉建筑物的总楼面面积时,总体平均绝对百分比误差为4.64%。验证结果还表明,使用所提方法估计的结构类型与具有结构类型不确定性的建筑物的实际结构类型之间的总体一致性可以达到97.54%,kappa系数为0.94。由于其良好的精度、显著的速度、可观的劳动力节省、可忽略不计的成本以及近乎实时地覆盖大面积的独特能力,这种“互联网+”方法在实际的地震损失风险降低挑战中可能具有广阔的前景。

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